Reliability, Consistency and Temporal Stability of Alberta Infant Motor Scale in Serbian Infants
Bibliographic record
Abstract
Our study aimed to analyze the reliability, consistency, and temporal stability of the Alberta Infant Motor Scale (AIMS) in Serbian infants. Additionally, we aimed to present a percentile distribution of AIMS in the tested population. The prospective study included 60 infants that were divided into three age groups: 0-3 months, 4-7 months, and 8-14 months. The Serbian version of AIMS was tested by two raters on two different occasions (test/retest) with a five day period between tests. The observed inter-rater reliability (intraclass correlation coefficient (ICC)) was more than 0.75 for all AIMS scores, except for standing (ICC 0.655 = moderate) in the age group of 4-7 months on retest between raters. The observed intra-rater reliability (ICC) was more than 0.75 for all AIMS scores except standing (ICC 0.655 = moderate) in the age group 4-7 months in test-retest for Rater One, and for sitting (ICC 0.671 = moderate) and standing (ICC 0.725 = moderate) in the age group between 0-3 months on test-retest for Rater Two. The Serbian version of AIMS was shown to have high consistency and high reliability with good to high temporal stability. Thus, it can be used in the evaluation of infants' motor development in Serbia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".